Literature DB >> 32987123

Deterministic Arterial Input Function selection in DCE-MRI for automation of quantitative perfusion calculation of colorectal cancer.

Christian Tönnes1, Sonja Janssen2, Alena-Kathrin Golla3, Tanja Uhrig3, Khanlian Chung3, Lothar R Schad3, Frank Gerrit Zöllner3.   

Abstract

Development of a deterministic algorithm for automated detection of the Arterial Input Function (AIF) in DCE-MRI of colorectal cancer. Using a filter pipeline to determine the AIF region of interest. Comparison to algorithms from literature with mean squared error and quantitative perfusion parameter Ktrans. The AIF found by our algorithm has a lower mean squared error (0.0022 ± 0.0021) in reference to the manual annotation than comparable algorithms. The error of Ktrans (21.52 ± 17.2%) is lower than that of other algorithms. Our algorithm generates reproducible results and thus supports a robust and comparable perfusion analysis.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Arterial input function; Colorectal cancer; Dynamic contrast enhanced MRI; Quantitative perfusion; Segmentation

Year:  2020        PMID: 32987123     DOI: 10.1016/j.mri.2020.09.009

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  1 in total

1.  Dynamic contrast-enhanced MRI parametric mapping using high spatiotemporal resolution Golden-angle RAdial Sparse Parallel MRI and iterative joint estimation of the arterial input function and pharmacokinetic parameters.

Authors:  Yousef Mazaheri; Nathanael Kim; Yulia Lakhman; Ramin Jafari; Alberto Vargas; Ricardo Otazo
Journal:  NMR Biomed       Date:  2022-03-14       Impact factor: 4.478

  1 in total

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